What it means
A process that produces output has a specification for that output, and any unit that does not meet it is defective. The defect rate measures how often that happens.
In its simplest form it is a percentage: 1,250 defective units in 50,000 produced is 2.5%. For high-volume processes where the rate is small, it is expressed as defects per million units, or, in the six sigma discipline, as defects per million opportunities, which counts the number of ways each unit could be defective and so allows comparison between simple and complex products.
The measure can be applied at any point in a process: incoming materials, each production stage, final inspection and, most importantly, the field, where defects that escaped inspection are found by customers. The distinction between a defective unit and a defect matters.
A unit may have several defects, and a process may be measured on either. Defective units are what the customer experiences and what must be reworked or scrapped; defects are what the process produces and what improvement work targets.
A related measure is first pass yield, the proportion of units that pass through a stage without any rework, which captures defects that are corrected before they reach final inspection and that a final defect rate would miss. A process with a 1% final defect rate but a 70% first pass yield is spending a great deal on rework that the headline figure hides.
The cost of defects, often called the cost of poor quality, has four parts. Internal failure costs are the rework, scrap, re-inspection and downtime caused by defects found before shipment.
External failure costs are the warranty claims, returns, repairs, credits, lost customers and reputational damage caused by defects found after shipment, and they are usually several times larger per defect than internal costs, because the product has been packed, shipped and used. Appraisal costs are the inspection and testing needed to find defects.
Prevention costs are the training, process design, supplier management and equipment maintenance that stop defects arising. The economics of quality rest on the observation that a dollar spent on prevention typically saves several in failure costs, and that catching a defect early costs a fraction of catching it late.
Reducing the defect rate begins with measuring it consistently and then finding out where the defects come from. A Pareto analysis usually shows that a small number of causes account for most defects: one machine, one supplier, one operation, one design feature.
Root cause analysis on those causes, using tools such as the five whys, cause-and-effect diagrams and statistical process control, identifies what to change. Process capability studies compare the natural variation of a process with the specification limits and show whether the process can meet the specification at all or whether it must be redesigned.
The improvement discipline, whether called six sigma, lean, total quality management or simply good engineering, is the same: measure, find the cause, fix the process rather than inspect the output. For a finance professional, the defect rate is a cost driver to be understood and a lever to be valued.
The cost of poor quality is rarely visible in the accounts, because rework labour sits in direct labour, scrap in materials, warranty in a provision and lost customers nowhere at all. Assembling it makes the case for quality investment on the same terms as any other project: an outlay to reduce the defect rate is justified by the failure costs it avoids and the customers it retains, and the finance function is the one that can put the numbers together.
In practice
Real-world examples.
Example
A pharmaceutical packaging line runs at 50 defects per million, because any labelling error is a regulatory event, and inspects 100% of output by camera to achieve it.
Example
An insurance company measures the defect rate of its claims processing as the percentage of claims that need rework because information was missing or entered wrongly, finds it is 18%, and treats it as a quality problem rather than a staffing one.
Example
A furniture maker's defect rate is 1.5% at final inspection but its first pass yield at the finishing stage is only 60%, and the rework in finishing is costing more than the scrap.
Think of it
“Defect rate shows what percentage of your production fails quality standards-your error frequency.
Formula
Calculation
Defect rate = Defective units / Total units inspected x 100
Defects per million opportunities (DPMO) = Number of defects / (Units inspected x Opportunities per unit) x 1,000,000
First pass yield = Units passing without rework / Units entering the stage x 100
Cost of poor quality = Internal failure costs + External failure costs (+ Appraisal + Prevention for the full cost of quality)
Worked example. A factory produces 50,000 units in a month; final inspection finds 1,250 defective units carrying 1,800 defects in total. Each unit has 8 features that could be defective.
- Defect rate = 1,250 / 50,000 = 2.5%
- DPMO = 1,800 / (50,000 x 8) x 1,000,000 = 4,500 defects per million opportunities, roughly a 4.1 sigma process
Internal failure cost. 70% of defective units can be reworked at $12 each; 30% are scrapped at $40 each.
- Rework: 875 units x $12 = $10,500; scrap: 375 units x $40 = $15,000; total $25,500 per 50,000 units
- Annual production is 600,000 units, so the internal failure cost is about $306,000 a year
External failure cost. Of the units shipped, 0.4% fail in the field and cost $150 each in warranty and handling.
- 600,000 x 0.4% = 2,400 failures x $150 = $360,000 a year
- Total cost of poor quality (failure costs only) = $306,000 + $360,000 = $666,000 a year, about 1.1% of the factory's $60,000,000 revenue
Improvement case. A process improvement programme costing $250,000 is expected to reduce the defect rate to 1.0% and the field failure rate to 0.2%.
- Internal failure cost falls by 60%: saving about $184,000 a year
- External failure cost halves: saving $180,000 a year
- Total saving about $364,000 a year against a one-off $250,000: payback under nine months, before counting the customers retainedCase study
Seen in the real world.
A contract electronics manufacturer assembling circuit boards for a large customer had a defect rate of 3.8% at final test, against the customer's contractual maximum of 2.0%. The customer, which represented $9,000,000 of the manufacturer's $30,000,000 revenue, gave notice that the contract would not be renewed unless the rate fell below the limit within six months. The manufacturer's finance director, asked to quantify the problem, found that on 2,000,000 boards a year the 3.8% rate meant 76,000 defective boards, each costing an average of $8 to diagnose and rework: $608,000 a year of rework cost that had been sitting invisibly in direct labour, in addition to the contract at risk.
The quality team's Pareto analysis of three months of defect data showed that 60% of the defects were solder bridges, and that 80% of those came from one of the four assembly lines. On that line the solder paste stencil was worn and the reflow oven's temperature profile had drifted from specification after a maintenance visit. Replacing the stencil and recalibrating the oven cost under $15,000 and cut the line's defect rate by three quarters within a week.
The next causes on the Pareto were component placement errors traced to one feeder type, and incoming component defects from a single supplier, each addressed in turn. Within four months the overall defect rate was 0.9%.
The financial result was a reduction in rework cost from $608,000 to about $144,000 a year (18,000 boards at $8), a saving of $464,000, and the retention of the $9,000,000 contract, which was renewed for three years. The programme's total cost, including the engineering time, was about $80,000.
The finance director's note to the board observed that the company had been spending more than half a million dollars a year on rework without anyone seeing it as a cost, and that the customer's ultimatum had done the company a favour by forcing it to look. The defect rate was added to the monthly board pack alongside margin, and the cost of poor quality became a line in the management accounts.
Watch out
Common mistakes.
- Measuring only the final inspection defect rate and missing the rework upstream, which first pass yield reveals and which often costs more than the scrap.
- Responding to a high defect rate with more inspection, which finds defects at higher cost rather than preventing them; the fix is in the process.
- Treating the cost of poor quality as invisible because it is spread across labour, materials and provisions; assembling it is what makes the case for quality investment.
Questions
People also ask.
What is the difference between defect rate and defects per million opportunities?
Defect rate counts defective units as a percentage of units; DPMO counts individual defects against the number of opportunities for a defect, which allows comparison between products of different complexity. A complex product with a 2% unit defect rate may have a low DPMO.
What is an acceptable defect rate?
It depends on the consequence of a defect. Consumer goods often run at 1% to 3%; automotive and electronics at tens or hundreds per million; pharmaceuticals and aerospace at near zero. The contractual limit with the customer, and the cost of a field failure, set the target.
How does the defect rate affect profit?
Through rework and scrap in the factory, warranty and returns in the field, inspection to find defects, and lost customers. These costs are rarely shown together in the accounts but can amount to several percent of revenue in a poorly controlled process.
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